What does "CoT" mean?
Table of Contents
Chain of Thought (CoT) is a method used to help large language models think through problems step-by-step. Instead of just giving a quick answer, the model works through the reasoning process, which can lead to better and more accurate results.
How It Works
When using CoT, the model is prompted to explain its thinking as it tackles a question or task. This means it writes down its thoughts in order, just like a person might do when figuring out a puzzle. By laying out the reasoning clearly, the model is more likely to arrive at the right conclusion.
Benefits
-
Improved Accuracy: By thinking through its answers, the model can find mistakes in its reasoning and correct them.
-
Clarity: CoT helps make the model's thought process clear, which is helpful for understanding how it arrived at its answer.
-
Better Performance on Tasks: In tests and competitions, models using CoT tend to perform better when facing complex challenges, especially in areas that require strategic thinking.
Overall, Chain of Thought is a useful tool for language models, making them more effective at handling tricky questions and tasks.